Course Contents - R Training

1. Overview of the R language

• Defining the R project
• Obtaining R
• Using the R console
• A sample R session

2. Generating R code

• Basic programming concepts
• Scripts
• Text editors for R
• Graphical User Interfaces (GUIs) for R
• Packages

3. Objects and data structures

• Variable classes (factor, numeric, logical, complex, missing)
• Vectors and matrices
• Data frames and lists
• Data sets included in R packages
• Summarizing and exploring data

4. Dealing with data

• Reading data from external files
• Storing data to external files
• Creating and storing R workspaces
• Basic exploratory graphics

5. Manipulating objects

• Mathematical operations
• Basic matrix computation
• Textual operations
• Searches, strings, and pattern matching
• Regular sequences
• Random sequences
• Sampling from distributions

6. Graphics

• More slicing and extracting data
• Basic plots
• Adding overlaid lines, text, etc.
• Graphical parameters
• Data exploration
• Summary graphics

7. Graphics, (advance)

• Basic graphical troubleshooting
• Brief introduction to regression graphics
• Generating data

8. Programming (basic)

• Functions
• Control structures
• Debugging

9. Hypothesis testing and data handling

• T-tests
• ANOVA
• Sorting/rearranging data structures

10. Linear & logistic regression

• General modeling syntax
• Extracting model results
• Confidence intervals
• Graphics for regression
• Tabular displays
• Extracting model results
• Confidence intervals
• Regression diagnostics

11. Graphics (intermediate)

• 3D graphics
• Graphics presentation
• Interactive graphics

12. Graphics (advanced)

• Animations
• High-density data displays
• Heatmaps & Partitioning graphics

13. Functions & resampling methods for model validation

• Applying functions
• Writing your own functions
• Modifying existing functions
• Permutation testing
• Bootstrapping
• Cross-validation methods